Part I: Mathematical foundations -- Tensor models: solution methods and applications / Shiqian Ma, Bo Jiang, Xiuzhen Huang, and Shuzhong Zhang -- Sparsity-aware distributed learning / Symeon Chouvardas, Yannis Kopsinis, and Sergios Theodoridis -- Optimization algorithms for big data with application in wireless networks / Mingyi Hong, Wei-Cheng Liao, Ruoyu Sun, and Zhi-Quan Luo -- A unified distributed algorithm for non-cooperative games / Jong-Shi Pang and Meisam Razaviyayn -- Part II: Big data over cyber networks -- Big data analytics systems / Ganesh Ananthanarayanan and Ishai Menache -- Distributed big data storage in optical wireless networks / Chen Gong, Zhengyuan Xu, and Xiaodong Wang -- Big data aware wireless communication: challenges and opportunities / Suzhi Bi, Rui Zhang, Zhi Ding, and Shuguang Cui -- Big data processing for smart grid security / Lanchao Liu, Zhu Han, H. Vincent Poor, and Shuguang Cui -- Part III: Big data over social networks -- Big data: a new perspective on cities / Riccardo Gallotti, Thomas Louail, Remi Louf, and Marc Barthelemy -- High-dimensional network analytics: mapping topic networks in Twitter data during the Arab Spring / Kathleen M. Carley, Wei Wei, and Kenneth Joseph -- Social influence analysis in the big data era: a review / Jianping Cao, Dongliang Duan, Liuqing Yang, Qingpeng Zhang, Senzhang Wang, and Feiyue Wang -- Part IV: Big data over biological networks -- Inference of gene regulatory networks: validation and uncertainty / Xiaoning Qian, Byung-Jun Yoon, and Edward R. Dougherty -- Inference of gene networks associated with the host response to infectious disease / Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, and Lawrence Carin -- Gene-set-based inference of biological network topologies from big molecular profiling data / Lipi Acharya and Dongxiao Zhu -- Large-scale correlation mining for biomolecular network discovery / Alfred Hero and Bala Rajaratnam.

Utilizing both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over large systems, making it essential reading for graduate students, scientific researchers and industry practitioners alike.